The Effect Of Stock Splits On The Returns Of Listed Companies At The Nairobi Securities Exchange

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This paper examined the effect of stock splits at the Nairobi Securities Exchange. This was achieved by studying eight companies that had undergone stock splits in the period 2000 to 2010. The study made use of the calculated returns to determine whether stock splits elicit any reaction in the Kenyan market. The study made use of daily prices for sample stock for the event window of 60 days, consisting of 30 days before and 30 days after the stock split. The event study methodology was employed in the determination of the effects of the split. A cross-sectional regression analysis was carried out using SPSS analysis program to determine the coefficients of the model. Returns of the eight selected companies were calculated and plotted on graphs against the days around the stock split. Daily average abnormal returns were then calculated for the event window of 60 days. The graphs were then analyzed to check for increased returns on days around the stock split. The abnormal returns were also plotted against the event window of
60days. The study found out that the Kenyan market reacts positively to stock splits, as shown by a general increase in returns around the stock split date. The study equally found out that on the split date and on days around the stock split, there was a positive average abnormal return. Results of the cumulative abnormal return indicated that there is a positive cumulative abnormal return across the different event windows. The study concluded that generally, the Kenyan market reacted positively to stock splits. The study recommends research on how the Kenyan market bonus issues especially those larger than 25% due to their similarity to stock splits. There is also need to research if the reasons brought forward by the theories for stock splits are true for the Kenyan market. The study suggests further research in the effect of future earnings and dividend expectations included in the information around stock split days. It also suggests further research on trading activity around the stock split and announcement date.